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Rhoda AI tweet 2110402702178148451 (content not retrievable at filing time)

TL;DR

Section titled “TL;DR”

A @rhodaai tweet (status id 2110402702178148451) shared in #research-external on 2026-10-14. The tweet body could not be retrieved at filing time — the fetcher returned only the X login wall and no cached mirror or unrolled thread was found via web search. Filed as a pointer stub so the Slack post is still linked to the Rhoda AI thread for later recovery; the probable topic is Rhoda AI’s Direct Video-Action Model line of work (see Direct Video-Action Models — Causal Video Models Are Data-Efficient Robot Policy Learners for the underlying method and Rhoda AI — Web-video pretraining scaling laws for robot policy learning (DVA) for the web-video pre-training scaling result from the same team), but no claims from this specific tweet should be relied on without recovering the original text.

Key claims

Section titled “Key claims”
  • (none — tweet body not retrievable at filing time)

Method

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Not applicable — tweet body not retrievable.

Results

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Not applicable — tweet body not retrievable.

Why it’s interesting

Section titled “Why it’s interesting”

Rhoda AI is the wiki’s lead instance of the “causal video model as the robot policy” thesis via Direct Video-Action Models — Causal Video Models Are Data-Efficient Robot Policy Learners (Direct Video-Action, Context Amortization, Leapfrog Inference), and the same team’s web-video pre-training scaling study was filed as Rhoda AI — Web-video pretraining scaling laws for robot policy learning (DVA). Any follow-up @rhodaai post is therefore worth tracking against those two anchors — but until the text is recovered, this stub exists only to preserve Patrick’s Slack pointer. If a researcher later recovers the content, prefer /bud refresh on this slug over appending inline.

See also

Section titled “See also”